Quantum mechanics is one of our most profound and successful theoretical frameworks for understanding the physical world. It continues to drive remarkable technological and theoretical breakthroughs, spanning computing, coding theory, cryptography, material science, and chemistry. In this talk, I will describe how the algorithmic lens has been pivotal in rigorously analyzing such quantum systems and revealed deeper structural properties that were previously inaccessible through traditional approaches.
Ainesh Bakshi is a Postdoctoral Fellow jointly appointed in the Mathematics and Computer Science departments at MIT. Prior to that, he obtained his PhD in Computer Science at CMU. He is broadly interested in theoretical computer science and quantum information. His main research thread revolves around using the algorithmic toolkit, consisting of iterative methods and convex hierarchies, to understand large quantum systems. These results have gained significant attention recently, including two Quanta articles, two QIP Invited Plenaries, a QIP Best Student Paper, and being featured in Quanta Magazine’s “Biggest Breakthroughs in Computer Science 2024.” He is also interested in extending this algorithmic toolkit and applying it to problems arising in high-dimensional statistics, privacy, metric embeddings, and numerical linear algebra.